首页|Findings from China University of Geosciences Advance Knowledge in Robotics (An Automatic Mapping Method of Navigation Map for Outdoor Road Scenes)
Findings from China University of Geosciences Advance Knowledge in Robotics (An Automatic Mapping Method of Navigation Map for Outdoor Road Scenes)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News-Research findings on robotics are disc ussed in a new report. According to newsreporting from Beijing, People's Republ ic of China, by NewsRx journalists, research stated, "In the process of autonomo us navigation of outdoor mobile robots, four modules are involved: perception, l ocalization,planning, and controlling. The perception module utilizes sensors s uch as cameras and radars based onvarious principles to analyze the robot's sur roundings in real-time."Our news correspondents obtained a quote from the research from China University of Geosciences:"The localization module uses GPS (Global Positioning System), IMU (Inertial Measurement Unit), andprior maps for real-time positioning analys is. The planning module plans optimal path based on theoutputs of the first two modules, and the controlling module directs the robot's chassis to move along the planned optimal path. For the localization module, the accuracy of GPS positi oning results heavilydepends on weather conditions and GPS signal receptions. E ven if the positioning results of imu areintegrated, the positioning accuracy s till cannot meet the needs of robot navigation. Therefore, usingprior maps for repositioning can compensate for this accuracy deficiency. The planning module a lsorequires path planning based on prior maps. If the a priori map storage is l arge, it will lead to difficulties inusage, maintenance, and updates. Therefore , it is crucial to research lightweight navigation map mappingmethods."
China University of GeosciencesBeijingPeople's Republic of ChinaAsiaEmerging TechnologiesMachine LearningRob otRobotics
NETL
NSTL
